Parallel architectures are continually increasing in performance and scale, while underlying algorithmic infrastructure often fail to take full advantage of available compute power. Within the context of MPI, irregular communication patterns create bottlenecks in parallel applications. One common bottleneck is the sparse dynamic data exchange, often required when forming communication patterns within applications. There are a large variety of approaches for these dynamic exchanges, with optimizations implemented directly in parallel applications. This paper proposes a novel API within an MPI extension library, allowing for applications to utilize the variety of provided optimizations for sparse dynamic data exchange methods. Further, the paper presents novel locality-aware sparse dynamic data exchange algorithms. Finally, performance results show significant speedups up to 20x with the novel locality-aware algorithms.

翻译：并行架构的性能与规模持续提升，但底层算法基础设施往往未能充分利用现有计算能力。在MPI框架下，不规则通信模式成为并行应用的瓶颈。其中常见的瓶颈是稀疏动态数据交换——在应用内部构建通信模式时经常需要此类操作。现有多种动态交换方法，其优化策略直接集成在并行应用中。本文提出一种基于MPI扩展库的新型API，使应用能够利用多种优化后的稀疏动态数据交换方法。此外，本文还提出了新颖的局部感知稀疏动态数据交换算法。性能测试结果表明，新提出的局部感知算法可实现最高20倍的显著加速比。